Basement AI lab captures 10,000 hours of brain scans to train thought-to-text AI models — largest known neural dataset collected from thousands of humans over six months

December 12, 2025

, By Tom’s Hardware

Basement AI lab captures 10,000 hours of brain scans to train thought-to-text AI models — largest known neural dataset collected from thousands of humans over six months

Share via:

A San Francisco start-up has spent the past six months running data-analytics-id=”inline-link” href=”https://condu.it/thought/10k-hours” target=”_blank” data-url=”https://condu.it/thought/10k-hours” referrerpolicy=”no-referrer-when-downgrade” data-hl-processed=”none” data-mrf-recirculation=”inline-link”>one of the more unusual data projects in AI. Conduit says it has collected roughly 10,000 hours of non-invasive neural data from “thousands of unique individuals” in a basement studio, forming what it believes is the largest neuro-language dataset assembled to date. The company is using the recordings to train thought-to-text AI models that attempt to decode semantic content from brain activity in the seconds before a participant speaks…

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

Previous News

I tested the OnePlus 15R vs iPhone 16e vs Pixel 9a in an 11-round camera shoot-out — here’s the winner

Next News

The Best Tech PCMag Editors Bought in 2025

Tom’s Hardware

Popular

More Like this

Basement AI lab captures 10,000 hours of brain scans to train thought-to-text AI models — largest known neural dataset collected from thousands of humans over six months

December 12, 2025

, Published By Tom’s Hardware

Basement AI lab captures 10,000 hours of brain scans to train thought-to-text AI models — largest known neural dataset collected from thousands of humans over six months

A San Francisco start-up has spent the past six months running data-analytics-id=”inline-link” href=”https://condu.it/thought/10k-hours” target=”_blank” data-url=”https://condu.it/thought/10k-hours” referrerpolicy=”no-referrer-when-downgrade” data-hl-processed=”none” data-mrf-recirculation=”inline-link”>one of the more unusual data projects in AI. Conduit says it has collected roughly 10,000 hours of non-invasive neural data from “thousands of unique individuals” in a basement studio, forming what it believes is the largest neuro-language dataset assembled to date. The company is using the recordings to train thought-to-text AI models that attempt to decode semantic content from brain activity in the seconds before a participant speaks…

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

Website Upgradation is going on for any glitch kindly connect at office@startupnews.fyi

Previous News

I tested the OnePlus 15R vs iPhone 16e vs Pixel 9a in an 11-round camera shoot-out — here’s the winner

Next News

The Best Tech PCMag Editors Bought in 2025

Tom’s Hardware

More like this

Popular

Block title